QTM 350 HW 5: World Development Indicators

Summary statistics

## summary statistics table
indicators = ["unemployment_rate","life_expectancy","gdp_per_capita"]
summary = df[indicators].describe().T
summary = summary[["count","mean","std","min","25%","50%","75%","max"]]
summary

	count	mean	std	min	25%	50%	75%	max
unemployment_rate	186.0	7.268661	5.827726	0.130000	3.500750	5.537500	9.45525	37.852000
life_expectancy	209.0	72.416519	7.713322	52.997000	66.782000	73.514634	78.47500	85.377000
gdp_per_capita	203.0	20345.707649	31308.942225	259.025031	2570.563284	7587.588173	25982.63005	240862.182448

-The gdp per capita distribution has a wide range of values. The maximum gdp per capita is more than 10x the minimum.

-The life expectancy variable is relatively concentrated — over half of the countries have a life expectancy between 70-80 years.

-The unemployment rate of countries is also concentrated with the mean being 7.27% and the 75% quantile being 9.46%. However, the maximum unemployment rate is 37.85%.

GDP vs. Life Expectancy

Figure 1: This figure is a scatter plot of GDP per Capita vs. Life Expectancy for countries in the dataset

As GDP increases, life expectancy increases. A higher GDP means more economic flourishing, allowing more of the country to have access to a healthier lifestyle.

10 Countries With the Highest Unemployment Rates

Many of the countries on this list are in Africa.

Thank You for Watching

A reference for the dataset is World Bank (1978). A reference towards inequality shown by the world indicators is from Pillarisetti (1997).

Pillarisetti, J Ram. 1997. “An Empirical Note on Inequality in the World Development Indicators.” Applied Economics Letters 4 (3): 145–47.

World Bank. 1978. World Development Indicators. World Bank.